Apify to Azure Synapse Integration

How Datrise loads Apify into Azure Synapse

Datrise syncs Apify's actors, runs, datasets, key-value stores, request queues, and run logs into Azure Synapse as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.

Sync is incremental: Datrise uses COPY into staging, then a MERGE on stable id, so re-runs update only what changed. Hash distribution on the join id with date partitioning on facts. Synapse dedicated pools reward good hash-distribution choices, so Datrise distributes on entity ids to avoid data-movement-heavy joins.

Ideal for Azure analytics estates feeding Power BI.

Endpoints

Apify: Web scraping and browser automation platform.

Azure Synapse: Microsoft analytics workspace with SQL pools.

How Apify entities map to Azure Synapse

Apify entity	Azure Synapse object	Notes
actors	`apify_actors`	id PK · custom fields → NVARCHAR(MAX) JSON columns
runs	`apify_runs`	id PK · linked to apify_actors
datasets	`apify_datasets`	id PK · linked to apify_actors
key-value stores	`apify_key_value_stores`	id PK · linked to apify_actors

FAQ

How does Datrise handle Apify's custom fields in Azure Synapse?

Flexible values are stored as NVARCHAR(MAX) JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Azure Synapse types.

How does the Apify to Azure Synapse sync stay up to date?

It runs incrementally — Datrise uses COPY into staging, then a MERGE on stable id.

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